9-oxo-ODE as a biomarker for healthy aging

ABSTRACT

Using NMR/MS based metabonomics and targeted lipidomics approaches the inventors have explored the metabolic phenotypes of aging and longevity in a cohort including centenarians, elderly and young adults. The inventors have identified biomarkers for a reduced risk of developing ageing related chronic inflammatory disorders and propose a method of diagnosing a lifestyle that allows delaying and/or avoiding ageing related chronic inflammatory disorders using 9-oxo-ODE as biomarker.

The present application is a continuation of PCT/EP2013/054325, filedMar. 5, 2013, which application claims priority to European ApplicationNo. 12160731.1, filed Mar. 22, 2012, and the disclosure of each suchapplication is hereby incorporated by reference in its entirety for allpurposes.

The present invention generally concerns a healthy lifestyle and theprevention of ageing related chronic disorders. In particular, thepresent invention concerns biomarkers and their use to detectimprovements in lifestyle. As such, the present invention provides forexample 9-oxo-octadecadienoic acid (9-oxo-ODE) as a biomarker and amethod for diagnosing a lifestyle that allows delaying and/or avoidingageing related chronic inflammatory disorders that uses the biomarker9-oxo-octadecadienoic acid (9-oxo-ODE).

Aging is defined as the time-dependent decline of functional capacityand stress resistance, associated with increased risk of morbidity andmortality. Additionally, the aging phenotype in humans is veryheterogeneous and can be described as a complex mosaic resulting fromthe interaction of a variety of environmental, stochastic andgenetic-epigenetic variables. Decades of research on aging have foundhundreds of genes and many biological processes that are associated tothe aging process, but at the same time, many fundamental questions arestill unanswered or are object of intense debate.

These questions are frequently not addressable by examining a singlegene or a single pathway, but are better addressed at a systemic level,capturing aging as a complex multi-factorial process. Moreover, ageingis accompanied by a chronic, low grade, inflammatory status, resultingfrom an imbalance between pro- and anti-inflammatory processes, apathogenic condition that has been revealed critical in the onset ofmajor age-related chronic diseases such as atherosclerosis, type 2diabetes, and neuro-degeneration.

Within this perspective, acquired healthy aging and longevity are likelythe reflection of not only a lower propensity to accumulate inflammatoryresponses, but also of efficient anti-inflammatory network development.In addition, there is a growing awareness of the importance of thevariation in the gut microbiota as its effects on the host mammaliansystem, having displayed direct influence in the etiology of severaldiseases such as insulin resistance, Crohn's disease, irritable bowelsyndrome, obesity, and cardiovascular disease.

Metabonomics is considered today a well-established system approach tocharacterize the metabolic phenotype, which results from a coordinatedphysiological response to various intrinsic and extrinsic parametersincluding environment, drugs, dietary patterns, lifestyle, genetics, andmicrobiome. Unlike gene expression and proteomic data which indicate thepotential for physiological changes, metabolites and their kineticchanges in concentration within cells, tissues and organs, represent thereal end-points of physiological regulatory processes.

Metabolomics had successfully been applied to study the modulation ofthe ageing processes following nutritional interventions, includingcaloric restriction-induced metabolic changes in mice, dogs, andnon-human primates. Specifically, in the canine population profoundchanges in gut microbiota metabolism were associated with ageing.Despite these findings, a comprehensive profiling of the molecularmechanisms affecting the aging process has not yet been reported.Moreover, metabolic phenotyping of longevity is still missing.

Consequently, it was the objective of the present invention to providethe art with a biomarker that can be detected easily and that allows itto diagnose a lifestyle that is likely to permit healthy ageing and thatin particular allows to delay and/or avoid ageing related chronicinflammatory disorders.

The present inventors were surprised to see that they could achieve theobjective of the present invention by the subject matter of theindependent claims. The dependant claims further develop the idea of thepresent invention.

Using a combined holistic 1H nuclear magnetic resonance (NMR)spectroscopy approach in urine, and targeted mass spectrometry (MS) andlipidomic approaches in serum, the inventors could detect changes in themetabolic profiles of a well defined aging cohort compromisingcentenarians, elderly, and young adults.

The selected aging group represents a homogeneous population of arestricted geographic area of Northern Italy, compromising young adults(31 years old in average), elderly (70 years old), and centenarianspeople (100 years old). Among the three aging groups, centenarians are awell accepted model of healthy aging and longevity [Sansoni P, et al.,Exp Gerontol. 2008; 43:61-65; Franceschi C, et al., Mech Ageing Dev.2007; 128:92-105; Cevenini E, et al., Expert Opin Biol Ther. 2008;8:1393-1405] and their acquired successful aging seems to be driven byan optimal balance between pro-inflammatory and anti-inflammatory forces[Franceschi C, et al., Mech Ageing Dev. 2007; 128:92-105].

The inventors were surprised to find profound differences between theelderly and centenarian phenotypes where dynamics of the interactionbetween intestinal microbiota and the host, and a neutral balanced ofinflammatory responses are much more pronounced in the longevityphenotype.

The inventors have characterized, by using a complementary NMR-MS-basedmetabolomics and lipidomic approach, in both urine and serum, themetabolic phenotype (metabotype) of aging and longevity.

Centenarians reach the very extremes of the human lifespan because of aunique capability to postpone disease and disability into their lateryears of life. Classical clinical parameters (Table 1) display thatcentenarians have very low incidence of insulin-resistance, haveanthropometric (BMI), metabolic (cholesterol, LDL-C, HDL-C,triglycerides), values that are optimal for their age. In addition,their cognitive function was measured using the Mini-Mental StateExamination (MMSE), displaying low incidence of severe cognitivedecline.

Specifically centenarians display a unique metabolic phenotype.Metabolic profiling of urine revealed that the longevity phenotype ishighly influenced by the gut microbiome as displayed by a higherexcretion of phenylacetylglutamine (PAG), p-cresol sulphate (PCS). Theinventors postulate that gut microbiota extensively catabolize proteinand aromatic amino acids, including phenylalanine and tyrosine, to formphenylacetylglutamine and p-cresol sulfate.

Comprehensive MS-based targeted metabonomics analysis revealed importantbiological changes associated to longevity and healthy aging in serum.Furthermore, between the three age groups centenarians are an attractivelongevity model to characterize as they reach the very extremes of thehuman lifespan because of a unique capability to postpone disease anddisability into their later years of life. Within age progression theinventors saw a decrease in lysophospatidylcholines (LPC 18:2, LPC20:4), with their concentration being more reduced in centenarians.Specifically, the decrease in LPC 18:0 appears to be specific tocentenarians. While it is imperative to note that LPC has differentspecies based on fatty acid chain length and degree of saturation, withdifferent physical and biological properties, phospholipids aregenerally pro-inflammatory [Aiyar N, et al., Mol Cell Biochem. 2007;295:113-120], with atherogenic properties [Schmitz G, et al.,Atherosclerosis. 2010; 208:10-18], and their increase levels is oftenseen in patients with type 2 diabetes [Rabini R A, et al., Diabetes.1994; 43:915-919].

Elderly centenarians display a balanced change in concentration ofseveral acyl-ether PC species with contents of three PC-O species, PC-O34:3, PC-O 36:4, PC-O 40:1 significantly decreased and two ether PCspecies, PC-O 32:1, PC-O 34:1, being significantly higher. While thephysiological role of ether phospholipids is less understood,plasmalogens containing a vinyl ether bond linking the sn-1 aliphaticchain to the glycerol backbone are the most abundant etherphospholipids. Here, the differences in the levels of acyl-etherphosphatidylcholine species might be due to differences in handlingoxidative damage.

Within age progression, an increase in sphingomyeline (SM) species isseen with marked increase in SM-24.1 and SM-16:0 in centenarians. Yet,the inventors found a specific, decrease concentration of SM24:0 andSM-OH 22:1 in centenarians. SM species are important cellular membraneconstituents which are tightly associated with cholesterol inconstruction, metabolism and transport, and which are enriched in lipidrafts. The physiological role of SM is still not clear as previousstudies have shown the relationship between elevated SM levels andatherosclerosis [Kummerow F A, et al., J Nutr Biochem. 2001;12:602-607], while others displayed that plasma sphingomyelin levelswere not associated with increased risk of CVD events. Lastly, whilethere were no significant changes for the levels of mostdiacyl-phosphatidylcholine species (PC-O), centenarians displayalterations in the individual levels of PC-0 36:2.

Changes in contents of PC and PC-O might have an impact on the activityof arachidonic acid metabolites synthesis (prostaglandins, thromboxanes,leukotrienes) which are key mediators and regulators of hostphysiological reactions, involved in oxidative stress, apoptosis, andmodulation of immune and inflammatory functions. Indeed, centenariansdisplay also a unique balanced network of lipid mediators with bothanti- and pro-inflammatory properties.

Compared to elderly, a higher concentration of leukotrines, LTB-4 andLTE-4, was seen. Centenarians display higher level of15-hydroxy-eicosatetraenoic acid (15-HETE), a major product of15-lipoxygenase (15-LOX) enzyme. 15-HETE inhibits 5-lipoxygenaseformation, decreases the production of leukotriene B4 and 12-HETE andsuppresses immune reactions. Compared to elderly, increase activation ofCYP pathway is also seen in centenarians, with increase generation of8,9-EpETrE and decrease concentration of 11,12-DiHETrE. EpETrE areimportant components of many intracellular signaling in both cardiac andextracardiac tissues. Studies have shown that EpETrEs displayanti-inflammatory effects by inhibiting the activation of nuclear factor(NF)-κB-mediated gene transcription. In addition, they displaythrombolytic and angiogenic properties within the vasculature. EpETrEscan be further metabolized by soluble epoxide hydrolase (sEH) todihydroxy-eicosatrienoic acids (DiHETrE).

In general, when EpETrEs are metabolized to DiHETrEs by sEH, theirbiological activities become less pronounced, therefore here thedecrease in concentration of 11,12-DHET might reveal a decreased effectsEH of its precursor 11,12-EpETrE. Centenarians display a markeddecrease in 9-HODE, biological active molecule, and a marker of lipidperoxidation, and 9-oxo-RODE, a stable oxidation product of linoleicacid, the generation of which is increased where oxidative stress isincreased. Most of the linoleic acid exists in esterified forms as PCand cholesteryl linoleate, both are major components of LDL, and arecontinuously exposed to many kinds of oxidative stresses to generatehydroxy and hydroperoxy species.

Increased levels of lipid oxidation products, such as 9-oxo ODE werepreviously detected in plasma samples of patients suffering rheumatoidarthritis, and arthrosclerosis.

Further, compared to elderly, centenarians display depletion ineicosapentanoic acid (EPA). While EPA can be synthesized in humans fromalpha-linoleic acid or in greater amount directly from oily fish or fishoil supplements, EPA can be transformed into n-3 eicosanoids, which havediverse functions. A depletion of EPA could display an increasebiosynthesis of n-3 eicosanoids.

Consequently the present invention relates in part to a method ofdiagnosing a lifestyle that allows delaying and/or avoiding ageingrelated chronic inflammatory disorders, comprising

obtaining a serum sample from a subject

determining the level of 9-oxo-ODE, in the sample, and

comparing the subject's 9-oxo-ODE level to a predetermined referencevalue,

wherein the predetermined reference value is based on an average serum9-oxo-ODE level in a control population, and wherein a lower serum9-oxo-ODE level in the sample compared to the predetermined referencevalue indicates an increased likelihood to delay and/or avoid ageingrelated chronic inflammatory disorders.

This method has for example the advantage that obtaining serum from asubject is a well established procedure. The actual diagnosis method canbe carried out in a serum sample outside the body.

The level of 9-oxo-ODE in the sample can be detected and quantified byany means known in the art. For example, mass spectroscopy, e.g,UPLC-ESI-MS/MS, or NMR spectroscopy, e.g. 1H-NMR spectroscopy, may beused. Other methods, such as other spectroscopic methods,chromatographic methods, labeling techniques, or quantitative chemicalmethods may be used as well.

The predetermined reference value is based on an average serum 9-oxo-ODElevel in a control population. The control population can be a group ofat least 3, preferably at least 10, more preferred at least 50 peoplewith a similar genetic background, age and an average health status.

The control population can also be the same person, so that thepredetermined reference value is obtained previously from the samesubject. This will allow a direct comparison of the present lifestyle toa previous lifestyle, for example, and improvements can be directlyassessed.

Typical ageing related chronic inflammatory disorders are well known tothose of skill in the art. A large part of the ageing phenotype isexplained by an imbalance between inflammatory and anti-inflammatorynetworks, which results in the low grade chronic pro-inflammatory statusof ageing, “inflamm-ageing” (Candore G., et al., Biogerontology. 2010October; 11(5):565-73).

Typical age related inflammatory disorders are atherosclerosis,arthritis, dementia, type 2 diabetes, osteoporosis, and cardiovasculardiseases, for example. For example for these disorders inflammation isseen as a possible underlying basis for the molecular alterations thatlink aging and age related pathological processes (Chung et al.,ANTIOXIDANTS & REDOX SIGNALING, Volume 8, Numbers 3 & 4, 2006, 572-581).

9-oxo-ODE may be used as the only marker for the purpose of the presentinvention.

While 9-oxo-ODE as sole marker is effective as a tool for the diagnosismethod of the present invention, the quality and/or the predictive powerof said diagnosis will be improved, if the diagnosis relies on more thanjust one marker.

Hence one or more other markers for the likelihood to delay and/or avoidageing related chronic inflammatory disorders may be used in combinationwith 9-oxo-ODE.

The inventors were surprised to see that also other biomarkers can beused to detect the likelihood to delay and/or avoid ageing relatedchronic inflammatory disorders.

As such the inventors have identified that increased serumconcentrations of

1-O-alkyl-2-acylglycerophosphocholine (PC-O) 32:1,

1-O-alkyl-2-acylglycerophosphocholine (PC-O) 34:1,

15-hydroxy-eicosatetraenoic acid (15-HpETE),

Leukotriene E4(LTE4), Leukotriene B4(4LTB), and/or

8,9-epoxyeicosatrienoic (8,9 EpETre)

allow diagnosing a lifestyle that allows delaying and/or avoiding ageingrelated chronic inflammatory disorders while decreased serumconcentrations of

Lysophosphatidylcholines (LPC) 18:0

Hydroxy-Sphingomyelin (SM-OH) 22:1,

Sphingomyeline (SM) 24:0,

1-O-alkyl-2-acylglycerophosphocholine (PC-O) 34:3,

1-O-alkyl-2-acylglycerophosphocholine (PC-O) 36:4,

1-O-alkyl-2-acylglycerophosphocholine (PC-O) 40:1,

Phosphatidylcholine (PC) 36:2,

hydroxyoctadecadienoic acid (9-HODE),

and/or

11,12-epoxyeicosatrienoic acid (11,12-DiHETre) allow diagnosing alifestyle that allows delaying and/or avoiding ageing related chronicinflammatory disorders.

The individual lipid species were annotated as follows:

[lipid class] [total number of carbon atoms]:[total number of doublebonds]. For example, PC 34:1 reflects a phosphatidylcholine speciescomprising 34 carbon atoms and 1 double bond.

Consequently, in the method of the present invention the precision ofthe diagnosis may be increased by also assessing whether theconcentration of one or more of the following biomarkers PC-O 32:1, PC-O34:1, 15-HpETE, LTE4, LTB4, 8,9 EpETre is increased in serum, and/orwhether the concentration of one or more of the following biomarkers LPC18:0, SM-OH 22:1, SM 24:0, PC-O 34:3, PC-O 36:4, PC-O 40:1, PC 36:2,9-HODE, 11,12-DiHETre is decreased in serum, compared to a referencevalue previously obtained.

The method of the present invention may comprise the assessment of atleast 2, at least 3, at least 4, at least 5, at least 6, at least 7, orat least 8 biomarkers.

For example, 9-oxo-ODE may be assessed along with SM-OH 22:1.

9-oxo-ODE may also be assessed along with SM 24:0.

9-oxo-ODE may be assessed along with PC-O 34:1.

9-oxo-ODE may be assessed along with LTE4.

9-oxo-ODE may be assessed along with PC-O 40:1.

9-oxo-ODE may be assessed along with SM-OH 22:1 and SM 24:0.

9-oxo-ODE may be assessed along with SM-OH 22:1, SM 24:0 and PC-O 40:1.

9-oxo-ODE 0 may be assessed along with SM-OH 22:1, SM 24:0, PC-O 40:1,and 9-HODE.

9-oxo-ODE 0 may be assessed along with SM-OH 22:1, SM 24:0, PC-O 40:1,9-HODE LPC 18:0.

9-oxo-ODE may be assessed along with SM-OH 22:1, SM 24:0, PC-O 40:1,9-HODE, LPC 18:0, and PC-O 34:1.

9-oxo-ODE may be assessed along with SM-OH 22:1, SM 24:0, PC-O 40:1,9-HODE, LPC 18:0, PC-O 34:1, and LTE4.

The advantage of assessing more than one biomarker is that the morebiomarkers are evaluated the more reliable the diagnosis will become.If, e.g., more than 1, 2, 3, 4, 5, 6, or 7 biomarkers exhibit theelevations or decreases in concentration as described above, this is astrong indication for an increased likelihood to delay and/or avoidageing related chronic inflammatory disorders.

Consequently, the method of the present invention may further comprisedetermining the level of at least one of SM-OH 22:1, SM 24:0, PC-O 40:1,9-HODE, LPC 18:0, PC-O 34:1, or LTE4 in the sample, and comparing thesubject's level of at least one of SM-OH 22:1, SM 24:0, PC-O 40:1,9-HODE, LPC 18:0, PC-O 34:1, or LTE4 to a predetermined reference value,wherein the predetermined reference value is based on average serumSM-OH 22:1, SM 24:0, PC-O 40:1, 9-HODE, 9-oxo-ODE, PC-O 34:1, or LTE4level in a control population, and wherein a lower serum LPC 18:0 levelin the sample and/or a lower serum SM-OH 22:1, SM 24:0, PC-O 40:1,9-HODE, or LPC 18:0 level in the sample compared to the predeterminedreference values indicate an increased likelihood to delay and/or avoidageing related chronic inflammatory disorders, and/or wherein elevatedserum PC-O 34:1 and/or LTE4 levels in the sample compared to thepredetermined reference values indicate an increased likelihood to delayand/or avoid ageing related chronic inflammatory disorders.

The precision of the diagnosis of the present invention may further beincreased by also assessing whether one or more of the followingbiomarkers PC-O 32:1, 15-HpETE, LTB4, 8,9 EpETre is increased in serum,and/or whether one or more of the following biomarkers PC-O 34:3, PC-O36:4, PC 36:2, 11,12-DiHETre are decreased in serum, compared to areference value previously obtained.

The method of the present invention may additionally or alternatively beused to diagnose a lifestyle that permits healthy and/or healthierageing.

Healthier ageing may be diagnosed by comparing the actual PAG and/or PCSlevels of to predetermined reference values, which were obtainedpreviously from the same subject. Hence, in this case the same subjectwill act as control population and improvements in lifestyle can be seendirectly, while eliminating uncertainties originating from slightlydifferent conditions for other average control populations.

The method of the present invention may also be used to diagnoselongevity; and/or the likelihood for longevity. This has the advantagethat the consequences of a healthier lifestyle can be directly detected,the maintenance of a healthy lifestyle can be monitored and an unhealthylifestyle can be corrected before the first clinical manifestations ofan unhealthy lifestyle occur.

The method of the present invention may further be used alternativelyand/or additionally to diagnose to diagnose healthier gutmicroflora-host interactions. The gut microbiome performs numerousimportant biochemical functions for the host, and disorders of themicrobiome are associated with many and diverse human disease processes(Kinross et al., Genome Medicine 2011, 3:14). Unfavorable gutmicroflora-host interaction may have many clinical manifestations, suchas systemic disease states, e.g., obesity and cardiovascular disease; orintestinal conditions, e.g. inflammatory bowel disease.

The gut microflora-host interactions may be diagnosed in any subject,but it may be of particular importance to monitor healthymicroflora-host interactions in adults or in elderly

Hence, the healthier gut microflora-host interactions may be to bediagnosed in the elderly.

A subject is considered as “elderly” if it has surpassed the first halfof its average expected lifespan in its country of origin, preferably,if it has surpassed the first two thirds of the average expectedlifespan in its country of origin, more preferably if it has surpassedthe first three quarters of the average expected lifespan in its countryof origin, most preferred if it has surpassed the first four fifths ofthe average expected lifespan in its country of origin.

For example, if the subject is a human, the method of the presentinvention may be to be carried out in adults of at least 45 years ofage, at least 60 years of age, or at least 75 years of age.

The subject to be tested with the method of the present invention may bea human or an animal, in particular a mammal, for example. Typicalanimals may be companion animals, such as cats or dogs of farm animals,for example.

The method of the present invention may additionally or alternatively beused to detect the consequences of a change in lifestyle. Here it may beadvantageous if the LPC 18:0 level and optionally the levels of theother biomarkers mentioned herein are compared to the LPC 18:0 level andoptionally the levels of the other biomarkers obtained previously fromthe subject, e.g., before the change in lifestyle or earlier during thechange in lifestyle.

Hence, the method of the present invention may be to diagnose ahealthier lifestyle, wherein the predetermined reference values arebased the serum 9-oxo-ODElevel and optionally the levels of the otherbiomarkers obtained from the subject before a change in lifestyle.

The change in lifestyle may be any change, such as a different job, moresleep, less alcohol, more challenges, less stress, less smoking, moresports, a different working and/or living environment, for example.

The change of lifestyle may also be a change in the diet.

The change in the diet may be for example the use of at least onenutritional product that was previously was not consumed or consumed indifferent amounts.

As such the method of the present invention may be used to test theeffectiveness of a new nutritional regimen, of nutritional productsand/or of medicaments.

Nutritional products may be for example products that claim to have aneffect on healthy ageing and/or on avoiding ageing related chronicinflammatory disorders.

Typically, nutritional products may be food products, drinks, pet foodproducts, food supplements, nutraceuticals, food additives ornutritional formulas.

The level of the biomarkers, such as the LPC 18:0 level and optionallythe levels of the other biomarkers in the sample can be detected andquantified by any means known in the art. For example, massspectroscopy, e.g, UPLC-ESI-MS/MS, or NMR spectroscopy, e.g. 1H-NMRspectroscopy, may be used.

Other methods, such as other spectroscopic methods, chromatographicmethods, labeling techniques, or quantitative chemical methods may beused as well.

The method of the present invention comprises comparing levels of9-oxo-ODE level and optionally the other biomarkers of a test subject topredetermined reference values that may be derived from the 9-oxo-ODElevel in serum and optionally the levels of other biomarkers fromcomparable control subjects.

The extent of the difference between the subject's 9-oxo-ODE level andoptionally level of the other biomarkers and the corresponding controlvalue is also useful for characterizing the extent of the risk andthereby, determining which subjects would benefit most from certaintherapies.

The reference value for 9-oxo-ODE and optionally for the otherbiomarkers is preferably measured using the same units used tocharacterize the level of LPC 18:0 and optionally the other biomarkersobtained from the test subject. Thus, if the level of the 9-oxo-ODE andoptionally the other biomarkers is an absolute value such as the unitsof 9-oxo-ODE in (ng/100 μl serum the reference value is also based uponthe units of 9-oxo-ODE in ng/100 μl serum in individuals in the generalpopulation or a selected control population of subjects.

Moreover, the reference value can be a single cut-off value, such as amedian or mean. Reference values of LPC 18:0 and optionally the otherbiomarkers in obtained serum samples, such as mean levels, medianlevels, or “cut-off” levels, may be established by assaying a largesample of individuals in the general population or the selectedpopulation and using a statistical model such as the predictive valuemethod for selecting a positivity criterion or receiver operatorcharacteristic curve that defines optimum specificity (highest truenegative rate) and sensitivity (highest true positive rate) as describedin Knapp, R. G., and Miller, M. C. (1992). Clinical Epidemiology andBiostatistics. William and Wilkins, Harual Publishing Co. Malvern, Pa.,which is incorporated herein by reference.

Skilled artesians will know how to assign correct reference values asthey will vary with gender, race, genetic heritage, health status orage, for example.

For example, the predetermined reference mean values may be

-   -   2 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 32:1,    -   7.80 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 34:1,    -   1.25 ng/100 μl serum for 15-hydroxy-eicosatetraenoic acid        (15-HpETE),    -   0.013 ng/100 μl serum for Leukotriene E4(LTE4),    -   0.020 ng/100 μl serum for Leukotriene B4(4LTB), and/or    -   0.070 ng/100 μl serum for 8,9-epoxyeicosatrienoic (8,9 EpETre)    -   16.07 μM for Hydroxy-Sphingomyelin (SM-OH) 22:1,    -   52.00 μM for Lysophosphatidylcholines (LPC) 18:0,    -   25.00 μM for Sphingomyeline (SM) 24:0,    -   5.07 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 34:3,    -   14.30 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 36:4,    -   1.41 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 40:1,    -   10.00 μM for Phosphatidylcholine (PC) 36:2,    -   0.34 ng/100 μl serum for hydroxyoctadecadienoic acid (9-HODE),    -   0.043 ng/100 μl serum for 9-oxo-octadecadienoic acid        (9-oxo-ODE), and/or    -   0.017 ng/100 μl serum for 11,12-epoxyeicosatrienoic acid        (11,12-DiHETre).

Higher or lower values are indicative for an increased likelihood todelay and/or avoid ageing related chronic inflammatory disorders, asdetailed above.

The present inventors were also surprised to find further biomarkers inurine for diagnosing a lifestyle that allows delaying and/or avoidingageing related chronic inflammatory disorders.

As such the inventors have identified that increased urineconcentrations of phenylacetylglutamine (PAG) and/or p-cresol sulphate(PCS) allow diagnosing a lifestyle that allows delaying and/or avoidingageing related chronic inflammatory disorders.

Phenylacetylglutamine (PAG) and/or p-cresol sulphate (PCS) may beassessed following the method of the present invention, with the onlydifference that a urine sample is used.

A urine sample has the advantage that it can be obtained and analyzednon-invasively.

The predetermined reference values for PAG and PCS can be determined bythose of ski line the art and max vary depending on the circumstances.For example, typical reference values may be 63 μmol/mmol creatinine forPCS and 81 μmol/mmol creatinine for PAG in urine. Higher values areindicative for an increased likelihood to delay and/or avoid ageingrelated chronic inflammatory disorders.

The present invention also extends to the discovery of a new biomarkerthat can be used in the diagnosis of a lifestyle that allows delayingand/or avoiding ageing chronic inflammatory disorders.

Consequently, the present invention comprises a biomarker for thediagnosis of a lifestyle that allows delaying and/or avoiding ageingchronic inflammatory disorders, wherein the biomarker is LPC 18:0.

This biomarker may be detected in serum, which has the advantage thatsamples to be tested can be obtained easily, possible while analyzingserum for other purposes.

Those skilled in the art will understand that they can freely combineall features of the present invention described herein, withoutdeparting from the scope of the invention as disclosed. In particular,features described for the method of the present invention may beapplied to the biomarker of the present invention and vice versa.

Those skilled in the art will also understand that while the biomarkersand their application in a diagnosis method is described herein as

-   -   diagnosing a lifestyle that allows to delay and/or avoid ageing        related chronic inflammatory disorders,    -   diagnosing a lifestyle that permits healthy ageing,    -   diagnosing longevity, and/or    -   diagnosing healthier gut microflora-host interactions,        the biomarkers can equally well be applied in a method for    -   diagnosing a lifestyle that favors the development of ageing        related chronic inflammatory disorders,    -   diagnosing a lifestyle that is likely to prevent healthy ageing,    -   diagnosing a risk for a shortened lifespan, and/or    -   diagnosing unhealthier gut microflora-host interactions.

In further aspects, the present invention provides methods for:

-   -   delaying, avoiding and/or preventing the development of ageing        related chronic inflammatory disorders,    -   promoting healthy ageing,    -   promoting longevity,    -   reducing a risk for a shortened lifespan,    -   promoting healthier gut microflora-host interactions, and/or    -   preventing unhealthier gut microflora-host interactions.

Typically such methods comprise a step of performing a diagnostic methodas described herein on a subject; and modifying a lifestyle of thesubject based on a result thereof. For instance, the method may comprisemodifying a lifestyle of the subject if a result of the diagnostic stepindicates:

-   -   an increased likelihood of the development of ageing related        chronic inflammatory disorders,    -   a lifestyle that is likely to prevent healthy ageing,    -   a risk for a shortened lifespan, and/or    -   unhealthier gut microflora-host interactions;        in the subject.

The modification in lifestyle in the subject may be any change asdescribed herein, e.g. a change in diet, a different job, more sleep,less alcohol, more challenges, less stress, less smoking, more sports, adifferent working and/or living environment, for example.

Preferably the change is the use of at least one nutritional productthat was previously was not consumed or consumed in different amounts,e.g. a nutritional product that has an effect on healthy ageing and/oron avoiding ageing related chronic inflammatory disorders (includingfood products, drinks, pet food products, food supplements,nutraceuticals, food additives or nutritional formulas).

Modifying a lifestyle of the subject also includes indicating a need forthe subject to change his/her lifestyle, e.g. prescribing, promotingand/or proposing a lifestyle change as described above to the subject.For instance, the method may comprise a step of administering orproviding at least one nutritional product as described above to thesubject.

Further advantages and features of the present invention are apparentfrom the following Tables, Examples and Figures.

Table 1 shows demographic, clinical characteristics of the recruitedaging cohort. Values are presented as mean (±SD) with the range inparentheses. 1 BMI=body mass index, 2 Diabetes mellitus: history ofdiabetes, fasting glucose plasma ≧126 mg/dl, 3 HDL=high densitylipoprotein, 4 LDL=low density lipoprotein, 5 MMSE=Cognitive functionmeasure using the Mini-Mental State Examination (MMSE). The score usedin the analysis was corrected by age and years of educations for oldpeople. MMSE for elderly cognitive impairment was graded as severe(score 0-17), mild (score 18-23), or not present (score 24-30). MMSE forcentenarians ≧20 absence of severe cognitive decline; <12 presence ofsevere cognitive decline. 6 CRP=C reactive protein 7 A-SAA=Serum amyloidA (SAA) proteins.

Table 2 display characteristic and model summary for the discriminantmodel between the selected aging groups.

Table 3 shows all significantly regulated metabolites in urine for the 3age groups detected by 1H-NMR. To gain semi-quantitative information,peak areas in the original spectra were integrated for these threemetabolites and differences with statistical significance were confirmedby using Wilcoxon Rank Sum test and marked as follow *p<0.05, **p<0.01,***p<0.001.

Table 4 display all significantly regulated metabolites in blood serumfor the 3 age groups detected by LC-MS. Values are expressed as meanvalues±SD, and marked as follows: *p<0.05, **p<0.01, ***p<0.001.

Table 5 display concentration levels (ng/100 μl) of inflammatory markersin serum for the 3 age groups analyzed by UPLC-ESI-MS/MS, and marked asfollows: *p<0.05, **p<0.01, ***p<0.001

FIG. 1 represent typical urine 600 Mhz profiles from the aging cohortdisplaying peaks arising from major low molecular weight molecules, suchas ketone bodies, organic acids, amino acids, as well as metabolitesderiving from both mammalian and gut microbial metabolism (PAG AND PCS).

FIG. 2A shows OPLS-DA score from urinary 1H-NMR spectra from elderly andcentenarians. FIG. 2B shows OPLS-DA score from young adults andcentenarians.

FIG. 3 shows coefficient plot derived from urinary 1H-NMR spectra fromelderly and centenarians.

FIG. 4 shows box plots on semi-quantitative information, derived frompeak areas (area under the curve) in the original spectra for PAG andPCS. Statistical significance were confirmed by using Wilcoxon Rank Sumtest and listed in table 3.

FIG. 5a, 5b shows differences in lipidomic profiles (mean lipidconcentrations) between the three aging time points measured by targetedUPLC-ESI-MS/MS metabonomic analysis. Box plots represent changes fromleft to right denoting centenarians, elderly and young individuals.Concentration is in μM. Mean values±SD from the targeted MS on the threeaging groups and statistical significance were confirmed by usingWilcoxon Rank Sum test and listed in table 4. Only significantdifferences are displayed and were assessed by Mann-Whitney U test.

FIG. 6 shows differences in lipidomic profiles (Results are expressed inng/100 μl and represent mean lipid concentrations) between the threeaging time points measured by targeted UPLC-ESI-MS/MS metabonomicanalysis. Box plots represent changes from left to right denotingcentenarians, elderly and young individuals. Mean values±SD from thetargeted MS on the three aging groups and Statistical significance wereconfirmed by using Wilcoxon Rank Sum test and listed in table 5. Onlysignificant differences are displayed and were assessed by Mann-WhitneyU test.

EXAMPLES Subjects and Study Groups

Each individual and their family gave informed consent for the study totake place. Overall, 541 subjects belonging to different age groups wereenrolled for this study in North Italy which includes Bologna, Florence,Parma, Milan. The centenarians were composed by 156 individuals (125females and 31 males), the elderly group was composed by 363 individuals(205 females and 158 males), the young adults group was composed by 22individuals (10 females and 12 males).

The study protocol was approved by the Ethical Committee ofSant'Orsola-Malpighi University Hospital (Bologna, Italy). The resultingbiological samples (serum and urine) were stored at −80° C. untilmetabolomic analysis.

Clinical Chemistry

Serum total, high density lipoprotein cholesterol (HDL) and triglycerideconcentrations were measured with respective enzymatic kits from RocheDiagnostics using an autoanalyzer (Roche Diagnostics Hitachi 917,Hitachi Ltd, Tokyo, Japan). Low density lipoprotein cholesterol (LDL)concentrations were calculated using the formula of Friedewald(Friedewald W T, et al., Clinical Chemistry 18 (6): 499-502). Cytokines,including mouse interferon gamma (IFNγ), interleukin 1 beta (IL-1β),interleukin 6 (IL-6), interleukin 10 (IL-10), interleukin 12 p70 (IL-12p70), keratinocyte derived chemokine (KC) and tumor necrosis factor(TNF), were measured using a mouse pro-inflammatory multiplex kit (MesoScale Discoveries, Gaithersburg, Md., USA). Assay was carried outaccording to the manufacturer's manual. High-sensitivity C-reactiveprotein (CRP) was measured using a sensitive double antibody sandwichELISA with rabbit antihuman CRP and peroxidase conjugated rabbitanti-human CRP.

Sample preparation for 1H NMR Spectroscopy. 1 ml of urine sample fromthe the three aging groups were dried in a freeze drying apparatus(Freeze-Dryer Fisher Scientific) and adjusted to pH 6.8 using 580 μL ofa phosphate buffer solution (KH2PO4, final concentration of 0.2 M)containing 1 mM of sodium 3-trimethylsilyl)-[2,2,3,3-2H4]-1-propionate(TSP), and introduced into 5 mm NMR tubes. Metabolic profiles weremeasured on a Bruker Avance III 600 MHz spectrometer equipped with aninverse 5 mm cryogenic probe at 300 K (Bruker Biospin, Rheinstetten,Germany). For each urine sample 1H NMR spectra were registered usingpulse sequences including a standard 1H detection with watersuppression. The standard spectra were acquired with a relaxation delayof 4 s and a mixing time tm of 100 ms. Acquired 1H NMR spectra wereprocessed using the Topspin software package (version 2.1; BrukerBiospin, Rheinstetten, Germany) and were referenced to the standard(TSP) at δ=0.0. The peak assignment to specific metabolites was achievedusing an internal library of compounds and the literature and confirmedby standard two-dimensional NMR spectroscopy (JRES, TOCSY, HSQC, HMBC)on selected samples. For statistical analysis all NMR spectra wereconverted into 12 K data points over the range of δ0.4-10.0 and importedinto the MATLAB software (version 7.11.0 (R2010b); The MathWorks Inc.,Natick, Mass.) excluding the water residue (water δ=4.7120-4.84). Thespectra were normalized to the total sum of all intensities within thespecified range.

Sample Preparation for Biocrates Life Sciences AbsoluteIDQ™ kitAnalysis.

The Biocrates Life Sciences AbsoluteIDQ™ kit was used for serum samplesfrom selected aging cohort as previously published (Romisch-Margl, W.,C. Prehn, R. Bogumil, C. Rohring, K. Suhre, J. Adamski, Procedure fortissue sample preparation and metabolite extraction for high-throughputtargeted metabolomics. Metabolomics, 2011. Online First). Well platepreparation and sample application and extraction were carried outaccording to the manufacturer's instructions. A final volume of 10 μl ofserum was loaded onto the provided 96-well plate, containingisotopically labeled internal standards. Liquid chromatography wasrealized on a Dionex Ultimate 3000 ultra high pressure liquidchromatography (UHPLC) system (Dionex AG, Olten, Switzerland) coupled toa 3200 Q TRAP mass spectrometer (AB Sciex; Foster City, Calif., USA)fitted with a TurboV ion source operating in electrospray ionization(ESI) mode. Sample extracts (20 μl) were injected two times (in positiveand negative ESI modes) via direct infusion using a gradient flow rateof 0-2.4 min: 30 μl/min, 2.4-2.8 min: 200 μl/min, 2.9-3 min: 30 μl/min.MS source parameters were set at: desolvation temperature (TEM): 200°C., high voltage: −4500 V (ESI−), 5500 V (ESI+), curtain (CUR) andnebuliser (GS1 and GS2) gases: nitrogen; 20, 40, and 50 psi;respectively, nitrogen collision gas pressure: 5 mTorr. MS/MSacquisition was realised in scheduled reaction monitoring (SRM) modewith optimised declustering potential values for the 163 metabolitesscreened in the assay. Raw data files (Analyst software, version 1.5.1;AB Sciex, Foster City, Calif., USA) were imported into the providedanalysis software MetIQ to calculate metabolite concentrations. List ofall detectable metabolites is available from Biocrates Life Sciences,Austria (http://biocrates.com). Sample preparation and inflammationmarkers quantification by UPLC-ESI-MS/MS using isotope dilutiontechnique.

Based on previously published work (Naga, et. al, PROG. LIPID RESEARCH,2001, 40, 199-299) a method to measure a panel of 63 inflammatorymarkers was developed in house. 300 μl of serum samples from remainingavailable biological material from the three age groups (n=15centenarians, n=30 elderly, n=50 young adults) were homogenized with 10μl of BHT-buffer (butylated hydroxytoluene; 79.2 mg/ml PBS) using theFastPrep® 24 system. For each sample a total of 50 μl of serum was mixedwith 5 μl of the internal standard solution (0.1 ng/μl). The mixture wasacidified by adding 15 μl of citric acid (IN). To precipitate theproteins, a volume of 550 μl of methanol/ethanol (1:1, v:v) was addedand samples were mixed during 15 min at 4° C. before being centrifuged(3500 rpm, 10 min, 4° C.). The organic phase was evaporated to drynessunder constant nitrogen flow and the residues were solubilised with 80μl water, followed by the addition of 20 μL of acetonitrile, beforebeing centrifuged at 3500 rpm for 1 min at 4° C. The supernatant wastransferred into LC-MS vials before analysis. Analyses were carried outby liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS).LC was realized on a Dionex Ultimate 3000 ultra pressure liquidchromatography (UPLC) system (Dionex AG, Olten, Switzerland). MSdetection was realized on a 5500 Q TRAP mass spectrometer (AB Sciex;Foster City, Calif., USA) operating in ESI mode. Gradientchromatographic separation was performed on an Acquity BEH C18 column(2.1×150 mm, 1.7 μm; Waters, Milford, USA). The injection volume was 5μl and the column was maintained at 50° C. The mobile phase consisted ofwater containing 1% acetic acid (eluent A) and acetonitrile (eluent B)at a constant flow rate set at 450 μl/min. Gradient elution started from20% B with a linear increase to 50% B at 6 min, from 50% to 95% B at 13min, hold for 3 min at 95% B, before going back to 20% B at 16.1 min andreequilibration of the column for additional 11 min. Analytes weremonitored in the scheduled selected reaction monitoring (scheduled SRM)mode provided within the Analyst software (version 1.5.1; AB Sciex,Foster City, Calif., USA). All mass transitions and MS source parametersare given in supplementary data. The SRM detection window time was setat 120 sec with a target scan time of 0.5 sec. Nitrogen was used ascurtain and desolvation gas at the respective pressure of CUR: 20, GS1:70, GS2: 20 (arbitrary unit). Block source temperature was maintained at600° C., with the respective voltages: ISV: −4000 V, EP: −10 V, CXP: −5V. A 15-points calibration curve was realized prior to sample analysisby measuring different dilutions of the standard solution (0-10 ng).Data processing was realized using Analyst software (version 1.5.1; ABSciex, Foster City, Calif., USA). Peak area ratio of each analyte versusits corresponding internal standard or surrogate marker was calculated.It is worth to mention that PGJ2, PGF2a, PGE2, PGE1, 15-oxo-HETE,15-deoxy-Δ12,14-PGJ2, 6-keto PGF1a, and 5-oxo-ETE were below theirdetection limit in serum samples and therefore were not taken intoaccount for statistical analysis.

Multivariate Data Analysis (MVA)

MVA was performed in several software environments. Thus, data importand pre-processing steps for both 1H NMR and targeted MS data were doneusing ‘in-house’ routines written in MATLAB (version 7.11.0, TheMathworks Inc., Natick, Mass., USA). In NMR data analysis OPLS-DA modelswere carried out by using the SIMCA-P+ software (version 12.0, UmetricsAB, Umeå, Sweden). Targeted MS data was analyzed by Random Forests byusing the package ‘randomForest’ (A. Liaw and M. Wiener (2002).Classification and Regression by randomForest. R News 2(3), 18-22)running in the R environment (R Development Core Team (2011). R: Alanguage and environment for statistical computing. R Foundation forStatistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URLhttp://www.R-project.org/.). Finally, univariate significance tests forconfirmation were also performed in R. Clinical characteristics of theaging cohort.

Physical and biochemical characteristics of the aging cohort are shownin Table 1. BMI (p<0.001), homeostatic model assessment (HOMA)(p<0.001), total cholesterol (p=0.001), triglycerides (p=0.004), HDL(p=0.001), and LDL (p=0.04) are lower in centenarians, while serumamyloid A (A-SAA) proteins (p<0.001), and C-reactive protein (CRP)(p<0.001) are higher in centenarians, compared to elderly. Elderlydisplay higher BMI (p<0.001), total cholesterol (p<0.001), triglycerides(p<0.001), LDL (p<0.05), and CRP (p<0.001), compared to youngindividuals.

Urine 600 MHz 1H-NMR from the available samples of the three aginggroups (92 centenarians, 283 elderly, and 21 young adults) was used formetabolic profiling. To explore age induce changes and metabolicdifferences between the three age groups and minimize any effects ofnonrelevant metabolite variability, supervised chemometric analysis ofthe urine NMR profiling was applied on the full resolution NMR data setfrom the three time-points. Ortohogonal Projection on LatentStructures-Discriminant Analysis (OPLS-DA) was carried out on unitvariance scaled data (FIG. 2A-B). The discriminant model betweencentenarians and young adults groups provided a validation error of theclassifier (expressed as area under the ROC curve, AuROC (Fawcett, T.,An introduction to ROC analysis, Pattern Recogn. Lett., 2006,27:861-874) of 1.0 by using a 13.7% of the spectral variance (R2X)(Table 2). Likewise, the model between centenarians and elderly groupsgenerated a model with an AuROC validation error of 0.93 using again a13.7% of the total X variance (Table 2). To determine the metabolicsignatures associated to the differences between age groups, loadings ofthe first predictive component of the OPLS-DA model were used, colorcoded according to the correlation coefficient of the variable [30](FIG. 3). Accordingly, the urine discriminant model between centenariansand elderly individuals displays relatively higher amount ofphenylacetylglutamine (PAG), p-cresol-sulfate (PCS). To gainsemi-quantitative information, peak areas in the original spectra wereintegrated for these three metabolites and differences with statisticalsignificance were confirmed by using Wilcoxon Rank Sum test (FIG. 4,Table 3). Together, the results display that the gut microbial is highlyimplicated in the longevity process. Targeted and quantitative LC-MSmetabonomics displayed aging-associated metabolic changes in serum.

To determine age related metabolic differences in serum a targetedLC-MS/MS metabonomic approach was applied on the available biologicalsamples from the 3 aging groups (143 centenarians, 90 elderly and 20young adults). Multivariate data analysis was performed using RandomForests (RF™) (Breiman, L., Random Forests, Machine Learning, 2001,45:5-32) on pre processed semi-quantitative data on 160 metabolites,including amino acids, sugars, acyl-carnitines, sphingolipids, andglycerophospholipids. Using the variable importance feature implementedin RF™, it was possible to determine the metabolic signature thatdiscriminates better the three aging groups. To assess the individualdiscriminant ability of each component of the signature, Wilcoxon Ranksum tests among the age groups were performed (all significantlyregulated metabolites are listed in Table 4). While the overallconcentration of glycerolphospholipids and sphingolipids increase anddecrease depending on the fatty acid composition, three consistenttrends become apparent: set of compounds that increase or decrease(statistically valid) with age such as decrease concentration oflysophospatidylcholines (LPC 18:2, LPC 20:4), increase levels of PC32:0, and increase concentration of sphingomyelins (SM 24:1, SM 16:0);(ii) set of compounds specific to centenarians only, with no statisticalchanges among elderly and young individuals, as decrease insphingomyelins and specific glycerophospholipids (SM-OH 22:1, LPC 18:0,SM 24:0, PC-O 34:3, PC-O 36:4, PC-O 40:1, PC 36:2) and increase inspecific glycerophospholipids (PC-O 32:1, PC-O 34:1).

In addition, over the remaining available serum samples from the 3 aginggroups (12 centenarians, 37 elderly and 18 young adults) a targetedLC-MS/MS method was employed to investigate concentration changes ineicosanoid synthesis. Here, RF™ on quantitative data displayedstatistical relevant changes among the three age groups (FIG. 6).Statistical significances among the age groups were assessed by Wilcoxonrank sum test (all significantly regulated metabolites are listed insupplementary Table 5). Centenarians display lower concentration of11,12-dihydroxy-eicosatrienoic acid (11,12-DiHETrE),9-hydroxy-octadecadienoic acid (9-HODE), and 9-oxo-octadecadienoic acid(9-oxo-ODE), while at the same time increase concentrations of15-hydroxy-eicosatetraenoic acid (15-HETE), and leukotriene E4 (LTE4).Compared to elderly levels of eicosapentaenoic acid (EPA) decreased incentenarians. Furthermore, pair-wise MRC analysis between centenariansand elderly was applied to maximize changes in these two age groupsdisplaying increase serum concentration levels of8,9-epoxyeicosatrienoic (8,9-EET) and leukotriene B4 (LTB4) incentenarians.

The present invention also provides further embodiments as disclosed inthe following numbered paragraphs:

-   -   1. A method of diagnosing a lifestyle that allows to delay        and/or avoid ageing related chronic inflammatory disorders,        comprising        -   obtaining a serum sample from a subject        -   determining the level of PC-O 40:1, in the sample, and        -   comparing the subject's PC-O 40:1 level to a predetermined            reference value,    -    wherein the predetermined reference value is based on an        average serum PC-O 40:1 level in a control population, and    -    wherein a decreased serum PC-O 40:1 level in the sample        compared to the predetermined reference value indicates an        increased likelihood to delay and/or avoid ageing related        chronic inflammatory disorders.    -   2. A method of diagnosing a lifestyle that allows to delay        and/or avoid ageing related chronic inflammatory disorders,        comprising        -   obtaining a serum sample from a subject        -   determining the level of SM-OH 22:1, in the sample, and        -   comparing the subject's SM-OH 22:1 level to a predetermined            reference value,    -    wherein the predetermined reference value is based on an        average serum SM-OH 22:1 level in a control population, and    -    wherein a lower serum SM-OH 22:1 level in the sample compared        to the predetermined reference value indicates an increased        likelihood to delay and/or avoid ageing related chronic        inflammatory disorders.    -   3. The method of paragraph 1 or paragraph 2, further comprising        -   determining the level of at least one of PC-O 40:1, SM-OH            22:1, LPC 18:0, SM 24:0, PC-O 34:1, 9-HODE, 9-oxo-ODE, or            LTE4 in the sample, and        -   comparing the subject's level of at least one of PC-O 40:1,            SM-OH 22:1, LPC 18:0, SM 24:0, PC-O 34:1, 9-HODE, 9-oxo-ODE,            or LTE4 to a predetermined reference value,    -    wherein the predetermined reference value is based on average        serum PC-O 40:1, SM-OH 22:1, LPC 18:0, SM 24:0, PC-O 34:1,        9-HODE, 9-oxo-ODE, or LTE4 level in a control population, and    -    wherein a decreased serum PC-O 40:1, SM-OH 22:1, LPC 18:0, SM        24:0, PC-O 40:1, 9-HODE, and/or 9-oxo-ODE level in the sample        compared to the predetermined reference values indicate an        increased likelihood to delay and/or avoid ageing related        chronic inflammatory disorders, and/or    -    wherein increased serum LTE4 and/or PC-O 34:1 levels in the        sample compared to the predetermined reference values indicate        an increased likelihood to delay and/or avoid ageing related        chronic inflammatory disorders.    -   4. The method of one of paragraphs 1 to 3, wherein the precision        of the diagnosis is increased by also assessing whether one or        more of the following biomarkers PC-O 32:1, 15-HpETE, LTB4, 8,9        EpETre is increased in serum, and/or whether one or more of the        following biomarkers PC-O 34:3, PC-O 36:4, PC 36:2,        11,12-DiHETre are decreased in serum, compared to a reference        value previously obtained.    -   5. An in vitro method of diagnosing a lifestyle that allows to        delay and/or avoid ageing related chronic inflammatory        disorders, comprising        -   obtaining a urine sample from a subject        -   determining the level of p-cresol sulphate (PCS), in the            sample, and        -   comparing the subject's PCS level to a predetermined            reference value,    -    wherein the predetermined reference value is based on an        average urine PCS level in a control population, and    -    wherein an elevated urine PCS level in the sample compared to        the predetermined reference value indicates an increased        likelihood to delay and/or avoid ageing related chronic        inflammatory disorders.    -   6. The method of paragraph 5, further comprising        -   determining the level of phenylacetylglutamine (PAG) in the            sample, and        -   comparing the subject's PAG level to a predetermined            reference value,    -    wherein the predetermined reference value is based on average        urine PAG level in a control population, and    -    wherein elevated urine PCS and PAG levels in the sample        compared to the predetermined reference values indicate an        increased likelihood to delay and/or avoid ageing related        chronic inflammatory disorders.    -   7. A non-invasive method of diagnosing a lifestyle that allows        to delay and/or avoid ageing related chronic inflammatory        disorders, comprising        -   obtaining a urine sample from a subject        -   determining the level of phenylacetylglutamine (PAG), in the            sample, and        -   comparing the subject's phenylacetylglutamine (PAG), level            to a predetermined reference value,    -    wherein the predetermined reference value is based on an        average urine PAG level in a control population, and    -    wherein an elevated urine PAG level in the sample compared to        the predetermined reference value indicates an increased        likelihood to delay and/or avoid ageing related chronic        inflammatory disorders.    -   8. The method of paragraph 7, further comprising        -   determining the level of p-cresol sulphate (PCS) in the            sample, and        -   comparing the subject's PCS level to a predetermined            reference value,    -    wherein the predetermined reference value is based on average        urine PCS level in a control population, and    -    wherein elevated urine PAG and PCS levels in the sample        compared to the predetermined reference values indicate an        increased likelihood to delay and/or avoid ageing related        chronic inflammatory disorders.    -   9. The method of one of paragraphs 1 to 8 to diagnose a        lifestyle that permits healthy ageing.    -   10. The method of one of paragraphs 1 to 9 to diagnose        longevity.    -   11. The method of one of paragraphs 1 to 10 to diagnose        healthier gut microflora-host interactions.    -   12. The method of paragraph 11, wherein the healthier gut        microflora-host interactions are diagnosed in elderly.    -   13. The method of one of paragraphs 1 to 12 to diagnose a        healthier lifestyle, wherein the predetermined reference values        are based on serum or urine levels obtained from the subject        before a change in lifestyle.    -   14. The method in accordance with paragraph 13, wherein the        change in lifestyle is a change in the diet.    -   15. The method in accordance with paragraph 14, wherein the        change in the diet is the use of at least one nutritional        product that was previously was not consumed or consumed in        different amounts.    -   16. The method in accordance with paragraph 14 or 15 to test the        effectiveness of a new nutritional regimen.    -   17. The method of one of paragraphs 1 to 16 wherein the levels        of the biomarkers are determined by ¹H-NMR and/or mass        spectrometry in the sample and in the reference.    -   18. The method of one of paragraphs 1 to 17 to diagnose a        healthier lifestyle, wherein the predetermined mean reference        mean values are        -   2 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 32:1,        -   7.80 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O)            34:1,        -   1.25 μg/100 μl serum for 15-hydroxy-eicosatetraenoic acid            (15-HpETE),        -   0.013 μg/100 μl serum for Leukotriene E4(LTE4),        -   0.020 μg/100 μl serum for Leukotriene B4(4LTB), and/or        -   0.070 μg/100 μl serum for 8,9-epoxyeicosatrienoic (8,9            EpETre)        -   16.07 μM for Hydroxy-Sphingomyelin (SM-OH) 22:1,        -   52.00 μM for Lysophosphatidylcholines (LPC) 18:0,        -   25.00 μM for Sphingomyeline (SM) 24:0,        -   5.07 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O)            34:3,        -   14.30 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O)            36:4,        -   1.41 μM for 1-O-alkyl-2-acylglycerophosphocholine (PC-O)            40:1,        -   10.00 μM for Phosphatidylcholine (PC) 36:2,        -   0.34 μg/100 μl serum for hydroxyoctadecadienoic acid            (9-ODE),        -   0.043 μg/100 μl for 9-oxo-octadecadienoic acid (9-oxo-ODE),            and/or        -   0.017 μg/100 μl serum for 11,12-epoxyeicosatrienoic acid            (11,12-DiHETre).    -   19. The method according to any of paragraphs 1 to 18, further        comprising:        -   obtaining a urine sample from a subject        -   determining the level of phenylacetylglutamine (PAG) and/or            p-cresol sulphate (PCS) in the sample, and        -   comparing the subject's phenylacetylglutamine (PAG) and/or            PCS level to a predetermined reference value,        -   wherein the predetermined reference value is based on an            average urine PAG and/or PCS level in a control population,            and wherein elevated urine PAG and/or PCS levels in the            sample compared to the predetermined reference values            indicate an increased likelihood to delay and/or avoid            ageing related chronic inflammatory disorders.    -   20. A biomarker for the diagnosis of a lifestyle that allows        delaying and/or avoiding ageing chronic inflammatory disorders,        wherein the biomarker is PC-O 40:1.    -   21. A biomarker for the diagnosis of a lifestyle that allows        delaying and/or avoiding ageing chronic inflammatory disorders,        wherein the biomarker is SM-OH 22:1.    -   22. The biomarker in accordance with paragraph 20 or 21, wherein        the biomarker is to be detected in serum.    -   23. A biomarker for the diagnosis of a lifestyle that allows        delaying and/or avoiding ageing chronic inflammatory disorders,        wherein the biomarker is phenylacetylglutamine (PAG).    -   24. A biomarker for the diagnosis of a lifestyle that allows        delaying and/or avoiding ageing chronic inflammatory disorders,        wherein the biomarker is p-cresol sulphate (PCS).    -   25. The biomarker in accordance with paragraph 23 or 24, wherein        the biomarker is to be detected in urine.    -   26. A method for diagnosing (i) a lifestyle that favors the        development of ageing related chronic inflammatory        disorders, (ii) a lifestyle that is likely to prevent healthy        ageing, (iii) a risk for a shortened lifespan, and/or (iv)        unhealthier gut microflora-host interactions, comprising        -   obtaining a serum sample from a subject        -   determining the level of PC-O 40:1 and/or SM-OH 22:1 in the            sample, and        -   comparing the subject's PC-O 40:1 and/or SM-OH 22:1 level to            a predetermined reference value,    -    wherein the predetermined reference value is based on an        average serum PC-O 40:1 and/or SM-OH 22:1 level in a control        population, and    -    wherein an increased serum PC-O 40:1 and/or SM-OH 22:1 level in        the sample compared to the predetermined reference value        indicates (i) a lifestyle that favors the development of ageing        related chronic inflammatory disorders, (ii) a lifestyle that is        likely to prevent healthy ageing, (iii) an increased risk for a        shortened lifespan, and/or (iv) unhealthier gut microflora-host        interactions.    -   27. A method for diagnosing (i) a lifestyle that favors the        development of ageing related chronic inflammatory        disorders, (ii) a lifestyle that is likely to prevent healthy        ageing, (iii) a risk for a shortened lifespan, and/or (iv)        unhealthier gut microflora-host interactions, comprising        -   obtaining a urine sample from a subject        -   determining the level of PAG and/or PCS in the sample, and        -   comparing the subject's PAG and/or PCS level to a            predetermined reference value,    -    wherein the predetermined reference value is based on an        average urine PAG and/or PCS level in a control population, and    -    wherein a lower urine PAG and/or PCS level in the sample        compared to the predetermined reference value indicates (i) a        lifestyle that favors the development of ageing related chronic        inflammatory disorders, (ii) a lifestyle that is likely to        prevent healthy ageing, (iii) an increased risk for a shortened        lifespan, and/or (iv) unhealthier gut microflora-host        interactions.    -   28. A method for (i) delaying, avoiding and/or preventing the        development of ageing related chronic inflammatory        disorders, (ii) promoting healthy ageing, (iii) promoting        longevity, (iv) reducing a risk for a shortened lifespan, (v)        promoting healthier gut microflora-host interactions,        and/or (vi) preventing unhealthier gut microflora-host        interactions, comprising:        -   (a) performing a diagnostic method as described in paragraph            26 or 27; and        -   (b) modifying a lifestyle of the subject if the subject            has (i) an increased likelihood of the development of ageing            related chronic inflammatory disorders, (ii) a lifestyle            that is likely to prevent healthy ageing, (iii) an increased            risk for a shortened lifespan, and/or (iv) unhealthier gut            microflora-host interactions.    -   29. A method according to paragraph 28, wherein the modification        in lifestyle in the subject comprises a change in diet.    -   30. A method according to paragraph 29, wherein the change in        diet comprises administering at least one nutritional product to        the subject that has an effect on healthy ageing and/or on        avoiding ageing related chronic inflammatory disorders.

TABLE 1 Factor Centenerians Elderly Young Demographic Gender,male/female 31/125 158/205 12/10 Age, years 100.9^(±)2 (99-111)70.4^(±)6 (55-88) 30.6^(±)5 (25-40) Clinical BMI¹, kg/m²  23.8⁺3.7(13.3-34.1)  26.9^(±)4.6 (16.7-54.7)  21.92^(±)2.1 (18.3.23.6) HOMA1.90^(±)2.8 (0.20-23)   3.3^(±)3.1 (0.20-28.9) n/a Diabetes², n  8 36n/a Cholesterol, mg/dl 188.2^(±)38.1 (110-318)  201.0^(±)38.8 (5-335)   162.3^(±)28.4 (123-207)  Triglycerides, mg/dl 119.6^(±)65.4 (50-535)  125.5^(±)63.1 (41-550)   71.1^(±)32.1 (28-143)  HDL³, mg/dl 47.4^(±)13.1(20-99)   55.8⁺21.1 (20-212)  51.3^(±)8.7 (38-66)  LDL⁴, mg/dl116.2^(±)36.1 (27-248)   120^(±)41.7 (12-248)  96.8^(±)30.1 (49-144) MMSE⁵  20.3^(±)6.4 (1.3-30.8)  27.3^(±)1.9 (1.3-31.0) n/a CRP⁶, mg/L  5.8^(±)6.1 (0.28-28.2)   2.8^(±)3.7 (0.11-25.7)   0.7^(±)0.4(0.28-2.03) Heart failure, n 44  4 0 Irregular heart rhythm, n 33 46 0Angina pectoris, n 25 12 0 A-SAA⁷, μg/ml     540^(±)706 (0.01-3859.4)158.2^(±)21.9.6 (0.01-1861.9) n/a Metabolomics Urine-¹H-NMR Gender,male/female 18/74  128/155 11/10 Age, years 100.9^(±)2 (99-111)70.1^(±)6 (55-88) 30.9^(±)5 (24-40) Serum-Targeted MS Gender,male/female 30/113 34/56 11/9  Age, years 100.9^(±)2 (99-111) 69.6^(±)6(56-86) 30.6^(±)5 (24-40) Lipidomics Serum-Targeted MS Gender,male/female 2/10 21/16 9/9 Age, years  101^(±)2 (99-104)  70^(±)6(59-78) 31.2^(±)5 (25-40)

TABLE 2 Overview R2X_((cum)) R2Y_((cum)) Q²Y AuROC Centenarians vs.Elderly 0.14 0.52 0.39 0.96 0.93 Centenarians vs. Young 0.14 0.86 0.751.00 1.00 Young vs. Elderly 0.05 0.21 0.09 0.92 0.81

TABLE 3 Age group Peak Integral Chemical Centenarians Elderly Young(a.u.) shift Mean ± SD Mean ± SD Mean ± SD PAG 2.34 (s)  9.93 ± 3.72***6.62 ± 2.59 5.89 ± 2.35 PCS 7.36 (m) 4.06 ± 1.53*** 2.62 ± 1.22 2.32 ±0.85

TABLE 4 Young Elderly Centenarians Metabolites [μM/l] Mean ± SD Mean ±SD Mean ± SD PC-O 32:1 2.02 ± 0.36   2 ± 0.51 2.35 ± 0.63*  PC-O 34:17.34 ± 1.07 7.88 ± 1.71 9.54 ± 2.19*** PC-O 34:3 5.73 ± 1.4  5.07 ± 1.713.94 ± 1.54*** PC-O 36:2 9.54 ± 1.75 9.58 ± 2.39 9.29 ± 2.26*  PC-O 36:414.48 ± 2.83  14.35 ± 3.55  12.39 ± 2.56*   PC-O 40:1 1.23 ± 0.23 1.41 ±0.41 1.02 ± 0.32*** LPC 18:0 52.18 ± 12.93  52 ± 13.5 40.4 ± 12.02** SM24:0 23.45 ± 4.37  25.64 ± 5.31  19.79 ± 4.92***  SM-OH 22:1 14.52 ±2.94  16.07 ± 3.37  11.51 ± 3.04*** 

TABLE 5 Metabolites [(ng/ 100 μl serum] Young Elderly Centenarians LTE40.015 ± 0.014 0.013 ± 0.011 0.035 ± 0.03*** LTB4 0.011 ± 0.014 0.019 ±0.047 0.016 ± 0.009*  EPA 0.097 ± 0.036 0.123 ± 0.052 0.078 ± 0.026**15-HpETE 1.512 ± 1.949 1.255 ± 1.245  3.348 ± 2.865*** 11,12-DiHETrE 0.02 ± 0.006 0.017 ± 0.004 0.016 ± 0.006*  9-oxo-ODE 0.042 ± 0.0280.043 ± 0.039  0.022 ± 0.013*** 9-HODE 0.348 ± 0.223 0.397 ± 0.677 0.204± 0.211** 8,9-EpETrE 0.067 ± 0.101 0.074 ± 0.186  0.113 ± 0.107***

What is claimed is:
 1. A method of diagnosing and treating an ageingrelated chronic inflammatory disorder in a subject, comprising:determining a level of 9-oxo-octadecadienoic acid (9-oxo-ODE) in a serumsample obtained from the subject; comparing the subject's 9-oxo-ODElevel in the serum sample to a predetermined reference value, whereinthe predetermined reference value is based on an average serum 9-oxo-ODElevel in a control population, wherein the control population is thesame subject or a group of at least three people with a similar geneticbackground, age, and an average health status, wherein the subject is ahuman adult of at least 45 years of age, and wherein the ageing relatedchronic inflammatory disorder is atherosclerosis, arthritis, dementia,type 2 diabetes, osteoporosis, or cardiovascular disease; diagnosing thesubject with an ageing related chronic inflammatory disorder when thesubject's 9-oxo-ODE level in the serum sample is higher than thepredetermined reference value; and administering to the diagnosedsubject at least one nutritional product that was not previouslyconsumed or was consumed in a different amount by the subject, therebytreating the ageing related chronic inflammator disorder.
 2. The methodof claim 1, further comprising: determining a level of at least one ofhydroxy-sphingomyelin (SM-OH) 22:1, sphingomyelin (SM) 24:0,1-O-alkyl-2-acylglycerophosphocholine (PC-O) 40:1,hydroxyoctadecadienoic acid (9-HODE), lysophosphatidylcholines (LPC)18:0, 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 34:1, or leukotrieneE4 (LTE4) in the serum sample; comparing the subject's level of at leastone of SM-OH 22:1, SM 24:0, PC-O 40:1, 9-HODE, LPC 18:0, PC-O 34:1, orLTE4 in the serum sample to a predetermined reference value, wherein thepredetermined reference value is based on an average serum SM-OH 22:1,SM 24:0, PC-O 40:1, 9-HODE, LPC 18:0, PC-O 34:1, or LTE4 level in acontrol population, and wherein the control population is the samesubject or a group of at least three people with a similar geneticbackground, age, and an average health status; and diagnosing thesubject with an ageing related chronic inflammatory disorder when thesubject's SM-OH 22:1, SM 24:0, PC-O 40:1, 9-HODE, or LPC 18:0 level inthe serum sample is higher than the predetermined reference value and/orthe subject's PC-O 34:1 and/or LTE4 level in the serum sample is lowerthan the predetermined reference value.
 3. The method of claim 2,wherein the predetermined reference value is 16.07 μM for SM-OH 22:1 inserum, 25.00 μM for SM 24:0 in serum, 1.41 μM for PC-O 40:1 in serum,0.34 ng/100 μl serum for 9-HODE, 52.00 μM for LPC 18:0 in serum, 7.80 μMfor PC-O 34:1 in serum, and/or 0.013 ng/100 μl serum for LTE4.
 4. Themethod of claim 1, wherein the method further comprises increasing theprecision of diagnosing the subject with an ageing related chronicinflammatory disorder by determining whether a level of one or morebiomarkers selected from the group consisting of1-O-alkyl-2-acylglycerophosphocholine (PC-O) 32:1,15-hydroxy-eicosatetraenoic acid (15-HpETE), leukotriene B4 (LTB4),8,9-epoxyeicosatrienoic (8,9 EpETre) is increased in the serum sample,and/or whether a level of one or more biomarkers selected from the groupconsisting of 1-O-alkyl-2-acylglycerophosphocholine (PC-O) 34:3,1-O-alkyl-2-acylglycerophosphocholine (PC-O) 36:4, phosphatidylcholine(PC) 36:2, and 11,12-epoxyeicosatrienoic acid (11,12-DiHETre) isdecreased in the serum sample, compared to a predetermined referencevalue based on an average serum level of the one or more biomarkers in acontrol population, wherein the control population is the same subjector a group of at least three people with a similar genetic background,age, and an average health status.
 5. The method of claim 4, wherein thepredetermined reference value is 2 μM for PC-O 32:1 in serum, 1.25ng/100 μl serum for 15-HpETE, 0.020 ng/100 μl serum for LTB4, 0.070ng/100 μl serum for 8,9 EpETre, 5.07 μM for PC-O 34:3 in serum, 14.30 μMfor PC-O 36:4 in serum, 10.00 μM for PC 36:2 in serum, and/or 0.017ng/100 μl serum for 11,12-DiHETre.
 6. The method of claim 1, wherein thesubject is an elderly subject.
 7. The method of claim 1, wherein thelevel of 9-oxo-ODE in the sample and the predetermined reference valueare determined by 1H-NMR and/or mass spectrometry.
 8. The method ofclaim 1, wherein the predetermined reference value is 0.043 ng/100 μlserum for 9-oxo-ODE.
 9. The method of claim 1, further comprising:determining a level of phenylacetylglutamine (PAG) and/or p-cresolsulphate (PCS) in a urine sample obtained from the subject; comparingthe subject's PAG and/or PCS level in the urine sample to apredetermined reference value, wherein the predetermined reference valueis based on an average urine PAG and/or PCS level in a controlpopulation, and wherein the control population is the same subject or agroup of at least three people with a similar genetic background, age,and an average health status; and diagnosing the subject with an ageingrelated chronic inflammatory disorder when the subject's PAG and/or PCSlevel in the urine sample is lower than the predetermined referencevalue.